What can artificial intelligence do for human health? Revolutionize the way we eat, potentially. An opinion article published in the New York Times on Saturday covers the idea of personalized nutrition, made possible by super advanced algorithms and artificial intelligence (A.I.).

The article “The A.I. Diet” is written by cardiologist Eric Topol, and he begins by describing his experience as one of more than a thousand participants in a two-week health study where a sensor and a smartphone app helped track everything he did: eating, sleeping, exercise, and more.

Topol’s data was analyzed by A.I. to ultimately produce a personalized diet algorithm. His results consisted of specific foods receiving a grade, like you would on a test. It seems to me that both his experience and the study design overall highlight the importance of understanding how different foods are good or bad for different people – i.e. blueberries affect me differently than they affect someone else with a different genetic code and lifetime of environmental exposures.

Interestingly, a version of Topol’s study exists as an actual test – commercially available – but analyzes gut microbiome only, not glucose levels or eating habits (here, but it is likely other companies sell something similar).

Topol points out that the main problem is that we often perpetuate the “idea that there is one optimal diet for all people.” More or less, any specific guidance that goes beyond Michael Pollan’s famous quote (and a personal favorite of mine), “Eat food, not too much, mostly plants” is assuming too much about the similarities between individuals, complex and important factors like microbiome status, genetics, and environmental history. Topol: “[This assumption] contradicts the remarkable heterogeneity of human metabolism, microbiome and environment.”

“We know surprisingly little about the science of nutrition.”

Why? Topol cites difficulty with high-quality randomized trials, which are vital for nutrition science (or any type of science for that matter).

“The more understanding we have of foods and nutrition, the more complex food and nutrient interactions become,” explains nutrition scientist Kristine Polley, PhD. “Therefore, controlled and well thought-out study designs are becoming essential to interpret and translate results. High-quality randomized clinical trials provide insight into how nutrients affect human physiology and allow for accurate and critical interpretation of the data collected and the opportunity to apply these outcomes to better overall human health and quality of life.”

Another issue specific to nutrition science studies is that experiments with food habits require strict diet adherence, and there is not always an effective or easy way to ensure study participants are actually following the study’s prescribed diet.

Thirdly, where does the money come from for these types of studies? Unfortunately, often from companies that benefit from the results of the studies, increasing the chances that the results will be swayed one way or the other or misconstrued. In Topol’s words:

“The field [of nutrition science] has been undermined by the food industry, which tries to exert influence over the research it funds.”

The future of individualized/personalized nutrition depends heavily on the success of dependable nutrition studies. This data is vital for building the sophisticated A.I. technology needed to analyze the mass amounts of data to determine each individual’s specific nutritional needs. So the question that remains unanswered is, can nutrition scientists get it together (and find the funding) to obtain the needed results? I think they can.